Volume Table of Contents

PROCEEDINGS VOLUME 9301

INTERNATIONAL SYMPOSIUM ON OPTOELECTRONIC TECHNOLOGY AND APPLICATION 2014 | 13-15 MAY 2014

International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition

Editor(s): Gaurav Sharma, Fugen Zhou, Jennifer Liu

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IN THIS VOLUME

2 Sessions, 129 Papers, 0 Presentations

Front Matter: Volume 9301 (1)

Image Processing and Pattern Recognition (128)

INTERNATIONAL SYMPOSIUM ON OPTOELECTRONIC TECHNOLOGY AND APPLICATION 2014

13-15 May 2014

Beijing, China

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Front Matter: Volume 9301

Front Matter: Volume 9301 Open Access

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930101 (2014) https://doi.org/10.1117/12.2180626

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Image Processing and Pattern Recognition

Wide-band gas leak imaging detection system using UFPA Paper

Wei-qi Jin, Jia-kun Li, Xiong Dun, Minglei Jin, Xia Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930102 (2014) https://doi.org/10.1117/12.2070654

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The leakage of toxic or hazardous gases not only pollutes the environment, but also threatens people's lives and property safety. Many countries attach great importance to the rapid and effective gas leak detection technology and instrument development. However, the gas leak imaging detection systems currently existing are generally limited to a narrow-band in Medium Wavelength Infrared (MWIR) or Long Wavelength Infrared (LWIR) cooled focal plane imaging, which is difficult to detect the common kinds of the leaking gases. Besides the costly cooled focal plane array is utilized, the application promotion is severely limited. To address this issue, a wide-band gas leak IR imaging detection system using Uncooled Focal Plane Array (UFPA) detector is proposed, which is composed of wide-band IR optical lens, sub-band filters and switching device, wide-band UFPA detector, video processing and system control circuit. A wide-band (3µm~12µm) UFPA detector is obtained by replacing the protection window and optimizing the structural parameters of the detector. A large relative aperture (F#=0.75) wide-band (3μm~12μm) multispectral IR lens is developed by using the focus compensation method, which combining the thickness of the narrow-band filters. The gas leak IR image quality and the detection sensitivity are improved by using the IR image Non-Uniformity Correction (NUC) technology and Digital Detail Enhancement (DDE) technology. The wide-band gas leak IR imaging detection system using UFPA detector takes full advantage of the wide-band (MWIR&LWIR) response characteristic of the UFPA detector and the digital image processing technology to provide the resulting gas leak video easy to be observed for the human eyes. Many kinds of gases, which are not visible to the naked eyes, can be sensitively detected and visualized. The designed system has many commendable advantages, such as scanning a wide range simultaneously, locating the leaking source quickly, visualizing the gas plume intuitively and so on. The simulation experiment shows that the gas IR imaging detection has great advantages and widely promotion space compared with the traditional techniques, such as point-contact or line-contactless detection.

The research on image processing technology of the star tracker Paper

Yu-ming Li, Chun-jiang Li, Ran Zheng, Xiao Li, Jun Yang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930103 (2014) https://doi.org/10.1117/12.2072128

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A real-time multi-scale 2D Gaussian filter based on FPGA Paper

Haibo Luo, Xingqin Gai, Zheng Chang, Bin Hui

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930104 (2014) https://doi.org/10.1117/12.2072284

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Design and implementation of ATCA-based 100Gbps DP-QPSK optical signal test instrument Paper

Shaojing Su, Jiangyi Qin, Zhiping Huang, Chenwu Liu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930105 (2014) https://doi.org/10.1117/12.2072981

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In order to achieve the receiving task of 100Gbps Dual Polarization-Quadrature Phase Shift Keying (DP-QPSK) optical signal acquisition instrument, improve acquisition performance of the instrument, this paper has deeply researched DP-QPSK modulation principles, demodulation techniques and the key technologies of optical signal acquisition. The theories of DP-QPSK optical signal transmission are researched. The DP-QPSK optical signal transmission model is deduced. And the clock and data recovery in high-speed data acquisition and offset correction of multi-channel data are researched. By reasonable hardware circuit design and software system construction, the utilization of high performance Advanced Telecom Computing Architecture (ATCA), this paper proposes a 100Gbps DP-QPSK optical signal acquisition instrument which is based on ATCA. The implementations of key modules are presented by comparison and argumentation. According to the modularization idea, the instrument can be divided into eight modules. Each module performs the following functions. (1) DP-QPSK coherent detection demodulation module; (2) deceleration module; (3) FPGA (Field Programmable Gate Array); (4) storage module; (5) data transmission module; (6) clock module; (7) power module; (8) JTAG debugging, configuration module; What is more, this paper has put forward two solutions to test optical signal acquisition instrument performance. The first scenario is based on a standard STM-256 optical signal format and exploits the SignalTap of QuartusII software to monitor the optical signal data. Another scenario is to use a pseudo-random signal series to generate data, acquisition module acquires a certain amount of data signals, and then the signals are transferred to a computer by the Gigabit Ethernet to analyze. Two testing results show that the bit error rate of optical signal acquisition instrument is low. And the instrument fully meets the requirements of signal receiving system. At the same time this design has an important significance in practical applications.

Multi-source remote sensing image fusion method based on sparse representation Paper

Xianchuan Yu, Guanyin Gao

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930106 (2014) https://doi.org/10.1117/12.2073191

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Pixel arrangement design of retina-like sensor based on forward motion imaging visual task Paper

Fan Wang, Fengmei Cao, Tingzhu Bai, Zhihu Luo, Yulu Su

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930107 (2014) https://doi.org/10.1117/12.2065109

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3D Gaussian bin based sparse representation for action recognition Paper

Min Jiang, Jun Kong, Yi-Ning Sun

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930108 (2014) https://doi.org/10.1117/12.2065915

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A new template matching method based on contour information Paper

Huiying Cai, Feng Zhu, Qingxiao Wu, Sicong Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930109 (2014) https://doi.org/10.1117/12.2065931

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Template matching is a significant approach in machine vision due to its effectiveness and robustness. However, most of the template matching methods are so time consuming that they can’t be used to many real time applications. The closed contour matching method is a popular kind of template matching methods. This paper presents a new closed contour template matching method which is suitable for two dimensional objects. Coarse-to-fine searching strategy is used to improve the matching efficiency and a partial computation elimination scheme is proposed to further speed up the searching process. The method consists of offline model construction and online matching. In the process of model construction, triples and distance image are obtained from the template image. A certain number of triples which are composed by three points are created from the contour information that is extracted from the template image. The rule to select the three points is that the template contour is divided equally into three parts by these points. The distance image is obtained here by distance transform. Each point on the distance image represents the nearest distance between current point and the points on the template contour. During the process of matching, triples of the searching image are created with the same rule as the triples of the model. Through the similarity that is invariant to rotation, translation and scaling between triangles, the triples corresponding to the triples of the model are found. Then we can obtain the initial RST (rotation, translation and scaling) parameters mapping the searching contour to the template contour. In order to speed up the searching process, the points on the searching contour are sampled to reduce the number of the triples. To verify the RST parameters, the searching contour is projected into the distance image, and the mean distance can be computed rapidly by simple operations of addition and multiplication. In the fine searching process, the initial RST parameters are discrete to obtain the final accurate pose of the object. Experimental results show that the proposed method is reasonable and efficient, and can be used in many real time applications.

Modifications in SIFT-based 3D reconstruction from image sequence Paper

Zhenzhong Wei, Boshen Ding, Wei Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010A (2014) https://doi.org/10.1117/12.2068708

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In this paper, we aim to reconstruct 3D points of the scene from related images. Scale Invariant Feature Transform( SIFT) as a feature extraction and matching algorithm has been proposed and improved for years and has been widely used in image alignment and stitching, image recognition and 3D reconstruction. Because of the robustness and reliability of the SIFT’s feature extracting and matching algorithm, we use it to find correspondences between images. Hence, we describe a SIFT-based method to reconstruct 3D sparse points from ordered images. In the process of matching, we make a modification in the process of finding the correct correspondences, and obtain a satisfying matching result. By rejecting the “questioned” points before initial matching could make the final matching more reliable. Given SIFT’s attribute of being invariant to the image scale, rotation, and variable changes in environment, we propose a way to delete the multiple reconstructed points occurred in sequential reconstruction procedure, which improves the accuracy of the reconstruction. By removing the duplicated points, we avoid the possible collapsed situation caused by the inexactly initialization or the error accumulation. The limitation of some cases that all reprojected points are visible at all times also does not exist in our situation. “The small precision” could make a big change when the number of images increases. The paper shows the contrast between the modified algorithm and not. Moreover, we present an approach to evaluate the reconstruction by comparing the reconstructed angle and length ratio with actual value by using a calibration target in the scene. The proposed evaluation method is easy to be carried out and with a great applicable value. Even without the Internet image datasets, we could evaluate our own results. In this paper, the whole algorithm has been tested on several image sequences both on the internet and in our shots.

A moving target detection algorithm based on GMM and improved Otsu method Paper

Zhe Zhao, Yingqing Huang, Xiaoyu Jiang, Xingpeng Yan

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010B (2014) https://doi.org/10.1117/12.2068911

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The FPGA realization of a real-time Bayer image restoration algorithm with better performance Paper

Huaping Ma, Shuang Liu, Jiangyong Zhou, Zunlie Tang, Qilin Deng, Hongliu Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010C (2014) https://doi.org/10.1117/12.2069192

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An image similarity measure method based on mathematical morphology Paper

Jinrong Zhong, Yuwen Zhou, Jiayu Lin

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010D (2014) https://doi.org/10.1117/12.2069293

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A new correlation parameter extraction method for searching mode sea clutter restraint Paper

Xujin Yuan, Yong Chen, Chao Wang, Hongcheng Yin, Jingping Yao, Zhiming Xu, Yongge Lu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010E (2014) https://doi.org/10.1117/12.2069459

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Review of development of laser active imaging technology in China and foreign countries Paper

Youchen Fan, Hongli Zhao, Yingcun Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010F (2014) https://doi.org/10.1117/12.2069625

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Improvement of wavelet threshold filtered back-projection image reconstruction algorithm Paper

Zhong Ren, Guodong Liu, Zhen Huang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010G (2014) https://doi.org/10.1117/12.2069632

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A new approach to blind PSF estimation based on Mallows' statistics Cp Paper

Feng Xue, Jiaqi Liu, Chenyang Mu, Min Zhao, Li Zhang, Shenghai Jiao

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010H (2014) https://doi.org/10.1117/12.2069676

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Pose estimation for one-dimensional object with general motion Paper

Jinbo Liu, Ge Song, Xiaohu Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010I (2014) https://doi.org/10.1117/12.2069782

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Our primary interest is in real-time one-dimensional object’s pose estimation. In this paper, a method to estimate general motion one-dimensional object’s pose, that is, the position and attitude parameters, using a single camera is proposed. Centroid-movement is necessarily continuous and orderly in temporal space, which means it follows at least approximately certain motion law in a short period of time. Therefore, the centroid trajectory in camera frame can be described as a combination of temporal polynomials. Two endpoints on one-dimensional object, A and B, at each time are projected on the corresponding image plane. With the relationship between A, B and centroid C, we can obtain a linear equation system related to the temporal polynomials’ coefficients, in which the camera has been calibrated and the image coordinates of A and B are known. Then in the cases that object moves continuous in natural temporal space within the view of a stationary camera, the position of endpoints on the one-dimensional object can be located and also the attitude can be estimated using two end points. Moreover the position of any other point aligned on one-dimensional object can also be solved. Scene information is not needed in the proposed method. If the distance between the endpoints is not known, a scale factor between the object’s real positions and the estimated results will exist. In order to improve the algorithm’s performance from accuracy and robustness, we derive a pain of linear and optimal algorithms. Simulations’ and experiments’ results show that the method is valid and robust with respect to various Gaussian noise levels. The paper’s work contributes to making self-calibration algorithms using one-dimensional objects applicable to practice. Furthermore, the method can also be used to estimate the pose and shape parameters of parallelogram, prism or cylinder objects.

Novel image detail enhancement technology for high dynamic range infrared detector Paper

Ning Liu, Caigao Zhu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010J (2014) https://doi.org/10.1117/12.2069802

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Robust fiber clustering of cerebral fiber bundles in white matter Paper

Xufeng Yao, Yongxiong Wang, Songlin Zhuang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010K (2014) https://doi.org/10.1117/12.2069899

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SAR target feature extraction and recognition based multilinear principal component analysis Paper

Liping Hu, Xiaoyu Xing

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010L (2014) https://doi.org/10.1117/12.2069953

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Focal length precise measurement method for optics system based on lunar imaging Paper

Yiyun Man, Haichao Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010M (2014) https://doi.org/10.1117/12.2070187

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Accurate matching method of multimodal image based on phase congruency and local mutual information Paper

Chunyang Zhao, Huaici Zhao, Gang Zhao

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010N (2014) https://doi.org/10.1117/12.2070198

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Overview and development about image scrambling degree evaluation Paper

Congli Wang, Zhi-Bin Chen, Na-Na Ding

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010O (2014) https://doi.org/10.1117/12.2070204

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An improved infrared image enhancement algorithm based on multi-scale decomposition Paper

Honghui Zhang, Haibo Luo, Xin-rong Yu, Qing-hai Ding

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010P (2014) https://doi.org/10.1117/12.2070296

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Design of video interface conversion system based on FPGA Paper

Heng Zhao, Xiang-jun Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010Q (2014) https://doi.org/10.1117/12.2070301

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Error analysis and compensation research of scale factor for MEMS gyroscope Paper

Chang-zheng Liu, Xiangjun Wang, Qi-jian Tang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010R (2014) https://doi.org/10.1117/12.2070304

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Fundamental matrix estimation for binocular vision measuring system used in wild field Paper

Nian Yan, Xiangjun Wang, Feng Liu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010S (2014) https://doi.org/10.1117/12.2070319

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40-Gbps optical backbone network deep packet inspection based on FPGA Paper

Yuan Zuo, Zhiping Huang, Shaojing Su

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010T (2014) https://doi.org/10.1117/12.2070344

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In the era of information, the big data, which contains huge information, brings about some problems, such as high speed transmission, storage and real-time analysis and process. As the important media for data transmission, the Internet is the significant part for big data processing research. With the large-scale usage of the Internet, the data streaming of network is increasing rapidly. The speed level in the main fiber optic communication of the present has reached 40Gbps, even 100Gbps, therefore data on the optical backbone network shows some features of massive data. Generally, data services are provided via IP packets on the optical backbone network, which is constituted with SDH (Synchronous Digital Hierarchy). Hence this method that IP packets are directly mapped into SDH payload is named POS (Packet over SDH) technology. Aiming at the problems of real time process of high speed massive data, this paper designs a process system platform based on ATCA for 40Gbps POS signal data stream recognition and packet content capture, which employs the FPGA as the CPU. This platform offers pre-processing of clustering algorithms, service traffic identification and data mining for the following big data storage and analysis with high efficiency. Also, the operational procedure is proposed in this paper. Four channels of 10Gbps POS signal decomposed by the analysis module, which chooses FPGA as the kernel, are inputted to the flow classification module and the pattern matching component based on TCAM. Based on the properties of the length of payload and net flows, buffer management is added to the platform to keep the key flow information. According to data stream analysis, DPI (deep packet inspection) and flow balance distribute, the signal is transmitted to the backend machine through the giga Ethernet ports on back board. Practice shows that the proposed platform is superior to the traditional applications based on ASIC and NP.

An evolutionary method to achieve stable superpixel tracking Paper

Wenxing Xi, Xinyi Tang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010U (2014) https://doi.org/10.1117/12.2070611

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Object tracking is a hot and hard problem in the computer vision study area.We deal with large objects,which are challenged in many aspects,such as the factors of lighting, size, posture, disturbance, occlusion, and so on.The superpixel tracking method has been proposed to deal with this problem. Unlike many other approaches, it is robust in all the mentioned aspects to some extent. It is very flexible to deal with non-rigid objects just like the meanshift of color histogram does,but can be more advanced, since it takes advantage of the segmented local color histogram. Here we first introduce the adaptive superpixel tracking algorithm, which is comprised by two parts, modeling and confidence mapping using the color features of superpixels.We model them by clustering, just like the "bags of words" method does, and build the cluster confidence.The model is adaptive since it just learns from some latest tracked frames, which can accumulate errors and lead to drift easily. So we propose a refined model, which incorporates the kalman filter's ideas to this problem, by integrating the current model and the new model as an evolutionary one, to better adapt to the object variation and disturbance in subsequent frames, thus achieve more stable tracking. The evolutionary model is achieved by reclustering the cluster centers of the two models, to make new cluster centers and new cluster confidences. We allocate different weight to them, if the current model gets more weight, then the evolutionary model will be more stable, otherwise it will be more adaptive. Finally we give some experiment comparisons between the evolutionary model and the adaptive one. For most cases, when the scene of the object is stable, namely there is no big sudden light change or color change, the evolutionary model outperforms the adaptive one. The reason is that the adaptive one easily learns from other objects. But when the scene suffers big sudden change, the evolutionary model can’t quickly adapt to it and get failed, while the adaptive one may make it. In a word, the method is devised to achieve more stable tracking for stable scene applications.

Research on color constancy computation based on YCbCr color space and gray surface Paper

Hong Wang, Jianfeng Yang, Bin Xue, Xingtao Yan, Xiaofen Liang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010V (2014) https://doi.org/10.1117/12.2070658

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Detection algorithm for glass bottle mouth defect by continuous wavelet transform based on machine vision Paper

Jinfang Qian, Changjiang Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010W (2014) https://doi.org/10.1117/12.2070674

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Research on the multi-criteria combination in automatic recognition of marking points Paper

Yan An, Keyan Dong

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010X (2014) https://doi.org/10.1117/12.2070685

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The real-time complex cruise scene motion detection system based on DSP Paper

Zhi-guo Wu, Ming-jia Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010Y (2014) https://doi.org/10.1117/12.2070700

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Dynamic target recognition is an important issue in the field of image processing research. It is widely used in photoelectric detection, target tracking, video surveillance areas. Complex cruise scene of target detection, compared to the static background, since the target and background objects together and both are in motion, greatly increases the complexity of moving target detection and recognition. Based on the practical engineering applications, combining an embedded systems and real-time image detection technology, this paper proposes a real-time movement detection method on an embedded system based on the FPGA + DSP system architecture on an embedded system. The DSP digital image processing system takes high speed digital signal processor DSP TMS320C6416T as the main computing components. And we take large capacity FPGA as coprocessor. It is designed and developed a high-performance image processing card. The FPGA is responsible for the data receiving and dispatching, DSP is responsible for data processing. The FPGA collects image data and controls SDRAM according to the digital image sequence. The SDRAM realizes multiport image buffer. DSP reads real-time image through SDRAM and performs scene motion detection algorithm. Then we implement the data reception and data processing parallelization. This system designs and realizes complex cruise scene motion detection for engineering application. The image edge information has the anti-light change and the strong anti-interference ability. First of all, the adjacent frame and current frame image are processed by convolution operation, extract the edge images. Then we compute correlation strength and the value of movement offset. We can complete scene motion parameters estimation by the result, in order to achieve real-time accurate motion detection. We use images in resolution of 768 * 576 and 25Hz frame rate to do the real-time cruise experiment. The results show that the proposed system achieves real-time processing requirements for the engineering applications.

Human recognition based on head-shoulder contour extraction and BP neural network Paper

Xiao-fang Kong, Xiu-qin Wang, Guohua Gu, Qian Chen, Wei-xian Qian

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010Z (2014) https://doi.org/10.1117/12.2070804

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A robust point set registration algorithm based on information geometry Paper

Xiaoqiang Hua, Ping Wang, Kefeng Ji, Yinghui Gao, Ruigang Fu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930110 (2014) https://doi.org/10.1117/12.2070836

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A new thin cloud removal algorithm in single airborne image Paper

Jing Wang, Junyong Fang, Xue Liu, Dong Zhao, Qing Xiao

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930111 (2014) https://doi.org/10.1117/12.2070934

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Facial expression recognition based on fused Feature of PCA and LDP Paper

Zhang Yi, Hou-lin Mao, Yuan Luo

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930112 (2014) https://doi.org/10.1117/12.2070953

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An on-line calibration algorithm for external parameters of visual system based on binocular stereo cameras Paper

Liqiang Wang, Zhen Liu, Zhonghua Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930113 (2014) https://doi.org/10.1117/12.2070973

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Stereo vision is the key in the visual measurement, robot vision, and autonomous navigation. Before performing the system of stereo vision, it needs to calibrate the intrinsic parameters for each camera and the external parameters of the system. In engineering, the intrinsic parameters remain unchanged after calibrating cameras, and the positional relationship between the cameras could be changed because of vibration, knocks and pressures in the vicinity of the railway or motor workshops. Especially for large baselines, even minute changes in translation or rotation can affect the epipolar geometry and scene triangulation to such a degree that visual system becomes disabled. A technology including both real-time examination and on-line recalibration for the external parameters of stereo system becomes particularly important. This paper presents an on-line method for checking and recalibrating the positional relationship between stereo cameras. In epipolar geometry, the external parameters of cameras can be obtained by factorization of the fundamental matrix. Thus, it offers a method to calculate the external camera parameters without any special targets. If the intrinsic camera parameters are known, the external parameters of system can be calculated via a number of random matched points. The process is: (i) estimating the fundamental matrix via the feature point correspondences; (ii) computing the essential matrix from the fundamental matrix; (iii) obtaining the external parameters by decomposition of the essential matrix. In the step of computing the fundamental matrix, the traditional methods are sensitive to noise and cannot ensure the estimation accuracy. We consider the feature distribution situation in the actual scene images and introduce a regional weighted normalization algorithm to improve accuracy of the fundamental matrix estimation. In contrast to traditional algorithms, experiments on simulated data prove that the method improves estimation robustness and accuracy of the fundamental matrix. Finally, we take an experiment for computing the relationship of a pair of stereo cameras to demonstrate accurate performance of the algorithm.

Blur kernel estimate in single noisy image deblurring Paper

Shijie Sun, Huaici Zhao, Bo Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930114 (2014) https://doi.org/10.1117/12.2071034

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Multiple moving objects detection with movement evidence region growing in spatial-temporal domain Paper

Tianxu Zhang, Gang Zhou, Chao Zhang, Hao Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930115 (2014) https://doi.org/10.1117/12.2071080

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Enhancement algorithm of color fog image based on the brightness adjustment of interception function and adaptive scale Paper

Li-jun Yun, Yin Gao, Junsheng Shi, Fei-yan Cheng

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930117 (2014) https://doi.org/10.1117/12.2071095

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Low-cost high performance adaptive optics real-time controller in free space optical communication system Paper

Shanqiu Chen, Chao Liu, Enyi Zhao, Hao Xian, Bing Xu, Yutang Ye

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930118 (2014) https://doi.org/10.1117/12.2071100

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Improved mean shift target tracking approach under the interference of background Paper

Xiaoran Guo, Shaohui Cui, Dan Fang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930119 (2014) https://doi.org/10.1117/12.2071320

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Improved dependent component analysis for hyperspectral unmixing with spatial correlations Paper

Yi Tang, Jianwei Wan, Bingchao Huang, Tian Lan

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011A (2014) https://doi.org/10.1117/12.2071409

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Fringes' impetus to positional measurement of stars Paper

Zhong-jie Zheng, Qing-yu Peng

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011B (2014) https://doi.org/10.1117/12.2071483

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An improved corner detection algorithm for image sequence Paper

Minqi Yan, Bianlian Zhang, Min Guo, Guangyuan Tian, Feng Liu, Zeng Huo

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011C (2014) https://doi.org/10.1117/12.2071559

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Fast 3D reconstruction of tool wear based on monocular vision and multi-color structured light illuminator Paper

Zhongren Wang, Bo Li, Yuebin Zhou

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011D (2014) https://doi.org/10.1117/12.2071796

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Low-light level image de-noising algorithm based on PCA Paper

Zhuang Miao, Xiuqin Wang, Panqiang Yin, Dongming Lu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011E (2014) https://doi.org/10.1117/12.2072039

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Asynchronous data fusion of infrared imaging and laser ranging for target tracking Paper

Jingya Hao, BingJian Wang, Jia Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011F (2014) https://doi.org/10.1117/12.2072040

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Multi-sensor image registration based on visual attention Paper

Feihong Wu, BingJian Wang, Xiang Yi, Min Li, Jingya Hao, Huixin Zhou

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011G (2014) https://doi.org/10.1117/12.2072050

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Electronic image stabilization algorithm based on PCA-SIFT feature matching and self-adaptive high-pass filtering Paper

Min Li, BingJian Wang, Xiang Yi, Jingya Hao, Feihong Wu, Hanlin Qin

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011H (2014) https://doi.org/10.1117/12.2072051

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SAR Sea ice classification which is based on wavelet character Paper

Xi Chen, Yi Kong, Xian-bin Zhao, Wen-jun Liu, Yang Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011I (2014) https://doi.org/10.1117/12.2072080

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Moving target detection method based on polarization characteristics under the condition of moving detector Paper

Eryou Ji, Guohua Gu, Lianfa Bai, Weixian Qian

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011J (2014) https://doi.org/10.1117/12.2072146

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Moving target detection is a important field of image processing. Because the existing algorithms are vulnerable to background disturbance’s interference in the case of moving detector, a moving target detection algorithm based on target’s polarization characteristics under the condition of the moving detector has been proposed in this paper. Firstly, for the problem of the target detection such as the movement of background and parallax which are caused by the moving detector, a moving target detection method under the condition of moving detector has been proposed. The method gets detector’s motion estimation and compensation parameters by using image feature points matching method, and uses background updating method to achieve target’s detection. Then LK optical flow method is used to get target’s movement information and detector’s movement information and model the target’s and background’s movement information. Eventually this method calculates the relevance of the background’s and target’s movement information model to achieve target detection. Secondly, for the moving target detection method could not solve the problem of Background disturbance which interferes the detection result, a target detection method fused target polarization characteristics has been proposed on the basis of moving target detection method under the conditions of the rotation detector. This method realizes the target detection algorithm based on target’s polarization characteristics under the condition of moving detector, by pre-processing the polarization images to solve the parallax’s effect, clustering and segmenting the pretreated polarization image to extract polarized target, and fusing the moving target detection method. The experiment result shows that this method can effectively detect moving targets with a strong polarization characteristics in the scene, while suppressing the interference brought by strong polarized but still region and weak polarized background disturbance in the sense.

Fast obstacle detection based on multi-sensor information fusion Paper

Linli Lu, Jie Ying

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011K (2014) https://doi.org/10.1117/12.2072152

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Infrared small target enhancement by using sequential top-hat filters Paper

Jianjun Zhou, Haoyin Lv, Fugen Zhou

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011L (2014) https://doi.org/10.1117/12.2072159

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Algorithm about speckle noise filtering in active laser imaging Paper

Chao Wang, Yong-tao Li, He Chen, Zhao-xian Liang, Yun Lan

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011M (2014) https://doi.org/10.1117/12.2072171

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Investigation on improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering Paper

Bangze Zeng, Youpan Zhu, Zemin Li, Dechao Hu, Lin Luo, Deli Zhao, Juan Huang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011N (2014) https://doi.org/10.1117/12.2072192

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Study on numerical evaluation method of sky background luminance Paper

Wei-Feng Liu, Yong Wang, Xiao-Hui Hou

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011O (2014) https://doi.org/10.1117/12.2072219

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A fast particle filter object tracking algorithm by dual features fusion Paper

Shou-wei Zhao, Wei-ming Wang, Sa-sa Ma, Yong Zhang, Ming Yu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011P (2014) https://doi.org/10.1117/12.2072238

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Study on mean shift tracking algorithm combined with tracking differentiator Paper

Chen Huang, Jianjun Wang, Li Xue, Xin Gao

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011Q (2014) https://doi.org/10.1117/12.2072254

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Research on simulation of target echo of laser fuse in the near field Paper

Yanjie Cui, Bida Su, Wenqiang Chen, Xiangyang Zhang, Deng Rong

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011R (2014) https://doi.org/10.1117/12.2072290

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In order to study the near-field target characteristic of the laser fuse, an algorithm based on the relationship of bidirectional reflectance distribution function and laser radar cross section per unit area is proposed to calculate the echo power of laser fuse in the near-field. The main research work in this paper involves the followings (1)Based on the theory of beam division, a mathematical description of the angular distribution of the detonator laser beam is given to depicted the mathematical model of Gaussian beam. (2)By using the scattering characteristics of rough surface as well as the geometry mesh model of the target, the relation formula between received power and transmitted power of remote system for a facet is derived. (3)Establishing the missile-target encounter model though the conversion from different coordinate systems. Then calculate the echo power of laser fuse by integrating those of the geometrical elements which are illuminated by laser beam during missile target encounter. Consequently, the received power in each channels of the laser fuse can be calculated. In addition, the proposed theoretical model in this paper is calibrated by actually-measured data. And the emulation results are with a good agreement with measured results. Based on the theoretical analysis methods proposed in former chapters, we have developed a program to compute the echo power. Finally , we consider a simplified missile model, and compute its echo power under different angle and different material as well as different miss distance and different target miss in azimuth. The results show that scattering peaks correspond to the points of the wings of the missile. In addition, the results change obviously when using different material .For instance, the results with aluminum material are almost 10 times than that of white paint when ignoring the influence of atmospheric attenuation. At the same time, the results are different under the different miss distance as well as target miss in azimuth. Numerical results prove the proposed method high efficiency and preciseness. It would be especially valuable in engineering application.

The color measurement system for spot color printing basing multispectral camera Paper

Nanbo Liu, Weiqi Jin, Qinmei Huang, Li Song

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011S (2014) https://doi.org/10.1117/12.2072383

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Research on imaging ranging algorithm base on constraint matching of trinocular vision Paper

Pan Ye, Li Li, Wei-Qi Jin, Yu-tong Jiang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011T (2014) https://doi.org/10.1117/12.2072386

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Lane detection and tracking based on improved Hough transform and least-squares method Paper

Peng Sun, Hui Chen

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011U (2014) https://doi.org/10.1117/12.2072393

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Polygon star identification based on ant colony algorithm Paper

Baolin Ma, Jie Wu, Hongbo Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011V (2014) https://doi.org/10.1117/12.2072394

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Fruit fly optimization based least square support vector regression for blind image restoration Paper

Jiao Zhang, Rui Wang, Junshan Li, Yawei Yang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011W (2014) https://doi.org/10.1117/12.2072397

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The goal of image restoration is to reconstruct the original scene from a degraded observation. It is a critical and challenging task in image processing. Classical restorations require explicit knowledge of the point spread function and a description of the noise as priors. However, it is not practical for many real image processing. The recovery processing needs to be a blind image restoration scenario. Since blind deconvolution is an ill-posed problem, many blind restoration methods need to make additional assumptions to construct restrictions. Due to the differences of PSF and noise energy, blurring images can be quite different. It is difficult to achieve a good balance between proper assumption and high restoration quality in blind deconvolution. Recently, machine learning techniques have been applied to blind image restoration. The least square support vector regression (LSSVR) has been proven to offer strong potential in estimating and forecasting issues. Therefore, this paper proposes a LSSVR-based image restoration method. However, selecting the optimal parameters for support vector machine is essential to the training result. As a novel meta-heuristic algorithm, the fruit fly optimization algorithm (FOA) can be used to handle optimization problems, and has the advantages of fast convergence to the global optimal solution. In the proposed method, the training samples are created from a neighborhood in the degraded image to the central pixel in the original image. The mapping between the degraded image and the original image is learned by training LSSVR. The two parameters of LSSVR are optimized though FOA. The fitness function of FOA is calculated by the restoration error function. With the acquired mapping, the degraded image can be recovered. Experimental results show the proposed method can obtain satisfactory restoration effect. Compared with BP neural network regression, SVR method and Lucy-Richardson algorithm, it speeds up the restoration rate and performs better. Both objective and subjective restoration performances are studied in the comparison experiments.

Facial expression recognition based on image Euclidean distance-supervised neighborhood preserving embedding Paper

Li Chen, Yingjie Li, Haibin Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011X (2014) https://doi.org/10.1117/12.2072401

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The multi-spectral radiation influence research between buildings Paper

Bo Li, Huai-ci Zhao, Shi-jie Sun

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011Y (2014) https://doi.org/10.1117/12.2072404

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A fast panoramic mosaic method based on position sensor Paper

Ningming Wang, Yuanhong Luo, Jia Zhai

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011Z (2014) https://doi.org/10.1117/12.2072411

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An improved multi-scale autoconvolution transform Paper

Chunyan Shao, Qinghai Ding, Haibo Luo

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930120 (2014) https://doi.org/10.1117/12.2072429

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Affine invariant feature computing method is an important part of statistical pattern recognition due to the robustness, repeatability, distinguishability and wildly applicability of affine invariant feature. Multi-Scale Autoconvolution (MSA) is a transformation proposed by Esa Rathu which can get complete affine invariant feature. Rathu proved that the linear relationship of any four non-colinear points is affine invariant. The transform is based on a probabilistic interpretation of the image function. The performance of MSA transform is better on image occlusion and noise, but it is sensitive to illumination variation. Aim at this problem, an improved MSA transform is proposed in this paper by computing the map of included angle between N-domain vectors. The proposed method is based on the probabilistic interpretation of N-domain vectors included angle map. N-domain vectors included angle map is built through computing the vectors included angle where the vectors are composed of the image point and its N-domain image points. This is due to that the linear relationship of included angles between vectors composed of any four non-colinear points is an affine invariance. This paper proves the method can be derived in mathematical aspect. The transform values can be used as descriptors for affine invariant pattern classification. The main contribution of this paper is applying the N-domain vectors included angle map while taking the N-domain vector included angle as the probability of the pixel. This computing method adapts the illumination variation better than taking the gray value of the pixel as the probability. We illustrate the performance of improved MSA transform in various object classification tasks. As shown by a comparison with the original MSA transform based descriptors and affine invariant moments, the proposed method appears to be better to cope with illumination variation, image occlusion and image noise.

Hemagglutinin outer contour detection methods based on regular hexagon bar template Paper

Miaomiao Tian, Wenbo Jing, Jin Duan, Xiaoman Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930121 (2014) https://doi.org/10.1117/12.2072431

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The registration of dual-modality ship target images based on edge extraction Paper

Weimin Zhang, Risheng Wang, Fugen Zhou

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930122 (2014) https://doi.org/10.1117/12.2072437

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The method for detecting diffusion ring diameter in Hemagglutinin measuring Paper

Wenbo Jing, Xue Liu, Jin Duan, Xiao-man Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930123 (2014) https://doi.org/10.1117/12.2072438

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People counting in classroom based on video surveillance Paper

Quanbin Zhang, Xiang Huang, Juan Su

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930124 (2014) https://doi.org/10.1117/12.2072445

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Currently, the switches of the lights and other electronic devices in the classroom are mainly relied on manual control, as a result, many lights are on while no one or only few people in the classroom. It is important to change the current situation and control the electronic devices intelligently according to the number and the distribution of the students in the classroom, so as to reduce the considerable waste of electronic resources. This paper studies the problem of people counting in classroom based on video surveillance. As the camera in the classroom can not get the full shape contour information of bodies and the clear features information of faces, most of the classical algorithms such as the pedestrian detection method based on HOG (histograms of oriented gradient) feature and the face detection method based on machine learning are unable to obtain a satisfied result. A new kind of dual background updating model based on sparse and low-rank matrix decomposition is proposed in this paper, according to the fact that most of the students in the classroom are almost in stationary state and there are body movement occasionally. Firstly, combining the frame difference with the sparse and low-rank matrix decomposition to predict the moving areas, and updating the background model with different parameters according to the positional relationship between the pixels of current video frame and the predicted motion regions. Secondly, the regions of moving objects are determined based on the updated background using the background subtraction method. Finally, some operations including binarization, median filtering and morphology processing, connected component detection, etc. are performed on the regions acquired by the background subtraction, in order to induce the effects of the noise and obtain the number of people in the classroom. The experiment results show the validity of the algorithm of people counting.

Image depth estimation from compressed sensing theory Paper

Guangdong Du, Cheng Zhang, Hong Cheng, Yan Liu, Sui Wei

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930125 (2014) https://doi.org/10.1117/12.2072454

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Facial expression recognition based on improved DAGSVM Paper

Yuan Luo, Ye Cui, Yi Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930126 (2014) https://doi.org/10.1117/12.2072481

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Spatial distorted target recognition based on improved MACH filter Paper

Yu Chen, Furong Huo, Liqin Zheng

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930127 (2014) https://doi.org/10.1117/12.2072504

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Joint transform correlator (JTC) can make targets recognized and located accurately, but the bottleneck technique of JTC is how to recognize spatial distorted targets in cluttered scene. This has restricted the development of the pattern recognition with JTC to a great extent. In order to solve the problem, improved maximum average correlation height (MACH) filter algorithm is presented in this paper. The MACH algorithm has powerful capability of recognition for spatial distorted targets (rotation and scale changed etc.). The controlling parameters of the synthesized filter are optimized in this paper, which makes the filter have higher distortion tolerance and can suppress cluttered noise effectively. When improved MACH filter algorithm in frequency domain is projected to space domain, the MACH reference template image can be obtained which includes various forms of distorted target image. Based on amounts of computer simulation and optical experiments, MACH reference template is proved to have the capability of sharpening the correlation peaks and expanding recognizing scope for distorted targets in cluttered scene. MATLAB software is applied to produce MACH reference image for the detected target images and conduct simulation experiments for its powerful calculation capability of matrix. In order to prove the feasibility of MACH reference in JTC and determine the recognition scope, experiments for an aircraft target in the sky are carried out. After the original image is processed by edge extraction, a MACH filter reference template is obtained in space domain from improved MACH filter in frequency domain. From simulation experiments, the improved MACH filter is proved to have the feasibility of sharpening correlation peaks for distorted targets. Optical experiments are given to verify the effectiveness further. The experiments show the angular distortion tolerance can reach up to ±15 degrees and scale distortion tolerance can reach up to ±23%. Within this scope, the spatial distorted aircraft can be recognized effectively. The actual effect of the improved MACH filter algorithm has been confirmed very well.

Application of automatic threshold in dynamic target recognition with low contrast Paper

Hua Miao, Xiaoming Guo, Yu Chen

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930128 (2014) https://doi.org/10.1117/12.2072569

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Hybrid photoelectric joint transform correlator can realize automatic real-time recognition with high precision through the combination of optical devices and electronic devices. When recognizing targets with low contrast using photoelectric joint transform correlator, because of the difference of attitude, brightness and grayscale between target and template, only four to five frames of dynamic targets can be recognized without any processing. CCD camera is used to capture the dynamic target images and the capturing speed of CCD is 25 frames per second. Automatic threshold has many advantages like fast processing speed, effectively shielding noise interference, enhancing diffraction energy of useful information and better reserving outline of target and template, so this method plays a very important role in target recognition with optical correlation method. However, the automatic obtained threshold by program can not achieve the best recognition results for dynamic targets. The reason is that outline information is broken to some extent. Optimal threshold is obtained by manual intervention in most cases. Aiming at the characteristics of dynamic targets, the processing program of improved automatic threshold is finished by multiplying OTSU threshold of target and template by scale coefficient of the processed image, and combining with mathematical morphology. The optimal threshold can be achieved automatically by improved automatic threshold processing for dynamic low contrast target images. The recognition rate of dynamic targets is improved through decreased background noise effect and increased correlation information. A series of dynamic tank images with the speed about 70 km/h are adapted as target images. The 1st frame of this series of tanks can correlate only with the 3rd frame without any processing. Through OTSU threshold, the 80th frame can be recognized. By automatic threshold processing of the joint images, this number can be increased to 89 frames. Experimental results show that the improved automatic threshold processing has special application value for the recognition of dynamic target with low contrast.

Study of flow field of burning particles in a pyrotechnic flame based on particle image and particle velocity Paper

R. Xue, H. Q. Xu, Y. Li, C. G. Zhu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930129 (2014) https://doi.org/10.1117/12.2072575

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No-reference quality assessment based on visual perception Paper

Junshan Li, Yawei Yang, Shuangyan Hu, Jiao Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012A (2014) https://doi.org/10.1117/12.2072586

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The visual quality assessment of images/videos is an ongoing hot research topic, which has become more and more important for numerous image and video processing applications with the rapid development of digital imaging and communication technologies. The goal of image quality assessment (IQA) algorithms is to automatically assess the quality of images/videos in agreement with human quality judgments. Up to now, two kinds of models have been used for IQA, namely full-reference (FR) and no-reference (NR) models. For FR models, IQA algorithms interpret image quality as fidelity or similarity with a perfect image in some perceptual space. However, the reference image is not available in many practical applications, and a NR IQA approach is desired. Considering natural vision as optimized by the millions of years of evolutionary pressure, many methods attempt to achieve consistency in quality prediction by modeling salient physiological and psychological features of the human visual system (HVS). To reach this goal, researchers try to simulate HVS with image sparsity coding and supervised machine learning, which are two main features of HVS. A typical HVS captures the scenes by sparsity coding, and uses experienced knowledge to apperceive objects. In this paper, we propose a novel IQA approach based on visual perception. Firstly, a standard model of HVS is studied and analyzed, and the sparse representation of image is accomplished with the model; and then, the mapping correlation between sparse codes and subjective quality scores is trained with the regression technique of least squaresupport vector machine (LS-SVM), which gains the regressor that can predict the image quality; the visual metric of image is predicted with the trained regressor at last. We validate the performance of proposed approach on Laboratory for Image and Video Engineering (LIVE) database, the specific contents of the type of distortions present in the database are: 227 images of JPEG2000, 233 images of JPEG, 174 images of White Noise, 174 images of Gaussian Blur, 174 images of Fast Fading. The database includes subjective differential mean opinion score (DMOS) for each image. The experimental results show that the proposed approach not only can assess many kinds of distorted images quality, but also exhibits a superior accuracy and monotonicity.

A position and attitude vision measurement system for wind tunnel slender model Paper

Lei Cheng, Yinong Yang, Bindang Xue, Fugen Zhou, Xiangzhi Bai

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012B (2014) https://doi.org/10.1117/12.2072604

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An optimized fast image resizing method based on content-aware Paper

Yan Lu, Kun Gao, Kewang Wang, Tingfa Xu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012C (2014) https://doi.org/10.1117/12.2072607

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IR and visual image registration based on mutual information and PSO-Powell algorithm Paper

Youwen Zhuang, Kun Gao, Xianghu Miu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012D (2014) https://doi.org/10.1117/12.2072614

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A hyperspectral anomaly detection algorithm based on orthogonal subspace projection Paper

Ying Liu, Kun Gao, Lijing Wang, Youwen Zhuang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012E (2014) https://doi.org/10.1117/12.2072616

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Spatial-temporal filtering method based on kernel density estimation in suppressing background clutter Paper

Yuexin Tian, Yinghui Liu, Kun Gao, Yuwen Shu, Guoqiang Ni

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012F (2014) https://doi.org/10.1117/12.2072618

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An adaptive point tracking method based on depth map for 2D-3D video conversion Paper

Yangdong Liu, Xinzhu Sang, Tianqi Zhao, Xunbo Yu, Guozhong Shi, Jing Liu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012G (2014) https://doi.org/10.1117/12.2072652

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The optimization of improved mean shift object tracking in embedded multicore DSP parallel system Paper

Li Tian, Fugen Zhou, Cai Meng, Congliang Hu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012H (2014) https://doi.org/10.1117/12.2072656

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Degradation and restoration of high resolution TDICCD imagery due to satellite vibrations Paper

Xiyang Zhi, Qingyu Hou, Xuan Sun, Wei Zhang, Liyuan Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012I (2014) https://doi.org/10.1117/12.2072691

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Identification method of satellite local components based on combined feature metrics Paper

Xi-yang Zhi, Qing-yu Hou, Wei Zhang, Xuan Sun

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012J (2014) https://doi.org/10.1117/12.2072693

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Multiple dim targets detection in infrared image sequences Paper

Tian-Lei Ma, Ze-lin Shi, Jian Yin, Bao-shu Xu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012K (2014) https://doi.org/10.1117/12.2072844

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A novel iris patterns matching algorithm of weighted polar frequency correlation Paper

Weijie Zhao, Linhua Jiang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012L (2014) https://doi.org/10.1117/12.2072856

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Projector calibration method based on optical coaxial camera Paper

Lili Xie, Shujun Huang, Zonghua Zhang, Feng Gao, Xiangqian Jiang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012M (2014) https://doi.org/10.1117/12.2072858

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The electromagnetic simulation of radar imaging of complicated satellites Paper

Wenjing Chen, Chunzhu Dong, Chaoying Huo, Hongmei Ren

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012N (2014) https://doi.org/10.1117/12.2072863

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Grassmann manifold based shape matching and retrieval under partial occlusions Paper

Chenxi Li, Zelin Shi, Yunpeng Liu, Baoshu Xu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012O (2014) https://doi.org/10.1117/12.2072864

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Visual fatigue modeling for stereoscopic video shot based on camera motion Paper

Guozhong Shi, Xinzhu Sang, Xunbo Yu, Yangdong Liu, Jing Liu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012P (2014) https://doi.org/10.1117/12.2072894

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A detection method of moving object based on hybrid difference Paper

Chuncai Wang, Lei Yan, Yingtao Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012Q (2014) https://doi.org/10.1117/12.2072899

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An automatic registration algorithm of infrared and visible images based on hybrid image features Paper

Yahong Zhang, Renbo Xia, Wei Wu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012R (2014) https://doi.org/10.1117/12.2073016

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Compression imaging based on Fourier transform optical system Paper

Jinfeng Lv, Huaici Zhao, Chunyang Zhao

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012S (2014) https://doi.org/10.1117/12.2073026

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Robust visual tracking of infrared object via sparse representation model Paper

Junkai Ma, Haibo Liu, Zheng Chang, Bin Hui

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012T (2014) https://doi.org/10.1117/12.2073033

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Non-uniformity correction for sequence-image based on local histogram specification Paper

Hongxia Gao, Humei Wang, Ting Jin, Xiaomeng Dong, Shitao Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012U (2014) https://doi.org/10.1117/12.2073052

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Fast small target tracking in IR imagery based on improved similarity measure Paper

Qingyu Hou, Xiyang Zhi, Lihong Lu, Huili Zhang, Wei Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012V (2014) https://doi.org/10.1117/12.2073057

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Rectangle object segmentation based on shape preserving and CV variational level set Paper

Junhui Feng, Yanghui Xiao, Ende Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012W (2014) https://doi.org/10.1117/12.2073059

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The speckle image reconstruction of the solar small scale features Paper

Libo Zhong, Yu Tian, Changhui Rao

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012X (2014) https://doi.org/10.1117/12.2073104

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A multi-sensor image fusion algorithm based on region-based selection and IHS transform Paper

Xinnan Fan, Ji Zhang, Min Li, Pengfei Shi, Bingbin Zheng, Xuewu Zhang, Zhixiang Yang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012Y (2014) https://doi.org/10.1117/12.2073105

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Robust and fast license plate detection based on the fusion of color and edge feature Paper

De Cai, Zhonghan Shi, Jin Liu, Chuanping Hu, Lin Mei, Li Qi

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012Z (2014) https://doi.org/10.1117/12.2073106

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A simple and efficient object detection method based on saliency measure for infrared radiation image Paper

Zhaolei Sun, Bin Hui

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930130 (2014) https://doi.org/10.1117/12.2073112

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A method of plane geometry primitive presentation Paper

Anbo Jiao, Haibo Luo, Zheng Chang, Bin Hui

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930131 (2014) https://doi.org/10.1117/12.2073114

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Human action recognition based on spatial-temporal descriptors using key poses Paper

Shuo Hu, Yuxin Chen, Huaibao Wang, Yaqing Zuo

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930132 (2014) https://doi.org/10.1117/12.2073115

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Traffic flow visualization based on line integral convolution Paper

Xuguang Zhang, Na Li, Can Cao, Xiaoli Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930133 (2014) https://doi.org/10.1117/12.2073118

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Long-term object tracking combined offline with online learning Paper

Mengjie Hu, Zhenzhong Wei, Guangjun Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930134 (2014) https://doi.org/10.1117/12.2073119

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Boat detection using vector accumulation of particle motion Paper

Xuguang Zhang, Na Li, Youyi Li, Xiaoli Li

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930135 (2014) https://doi.org/10.1117/12.2073122

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Fast object reconstruction in block-based compressive low-light-level imaging Paper

Jun Ke, Dong Sui, Ping Wei

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930136 (2014) https://doi.org/10.1117/12.2073123

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GPU-based parallel optimization implement of phase diversity Paper

Quan Zhang, Hua Bao, Changhui Rao, Zhenming Peng

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930137 (2014) https://doi.org/10.1117/12.2073135

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Point target enhancement based on temporal-spatial over-sampling and image filtering Paper

Ting Jin, Humei Wang, Xiaomeng Dong, Shitao Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930138 (2014) https://doi.org/10.1117/12.2073155

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Design of automatic image measuring system based on RTX simulation system Paper

Wei Gao, Yi Zeng, Yan Dong, Ye Gu, Guangheng Tong

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930139 (2014) https://doi.org/10.1117/12.2073163

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Adaptive infrared-image details enhancement technology Paper

Shi-yong Guo, Yi Zhang, Lian-fa Bai, Qian Chen

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013A (2014) https://doi.org/10.1117/12.2073166

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Robust detection of key point of a building for infrared imaging sequence Paper

Jinshen Wang, Fugen Zhou, Bindang Xue, Xiangzhi Bai

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013B (2014) https://doi.org/10.1117/12.2073169

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The research of infrared image enhancement algorithm based on human vision Paper

Chen Wang, Sili Gao, Xinyi Tang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013C (2014) https://doi.org/10.1117/12.2073170

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Center determination for trailed sources in astronomical observation images Paper

Jun Ju Du, Shao Ming Hu, Xu Chen, Di Fu Guo

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013D (2014) https://doi.org/10.1117/12.2073178

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A color fusion method of infrared and low-light-level images based on visual perception Paper

Jing Han, Minmin Yan, Yi Zhang, Lianfa Bai

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013E (2014) https://doi.org/10.1117/12.2073183

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An adaptive unsupervised hyperspectral classification method based on Gaussian distribution Paper

Jiang Yue, Jing-wei Wu, Yi Zhang, Lian-fa Bai

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013F (2014) https://doi.org/10.1117/12.2073195

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3D surface reconstruction from range slices Paper

Mingming Wang, Feng Zhu, Ying-ming Hao

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013G (2014) https://doi.org/10.1117/12.2073200

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An ISAR imaging algorithm for the space satellite based on empirical mode decomposition theory Paper

Tao Zhao, Chun-zhu Dong

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013H (2014) https://doi.org/10.1117/12.2073204

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Extraction of contour based on zero-crossing feature and contour measure Paper

Hanyu Hong, Jie Song, Li Zhang, Xiahua Zhang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013I (2014) https://doi.org/10.1117/12.2073220

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Simulation of the atmospheric turbulence image reconstruction based on compressed sensing Paper

Dong Li, Hongzhen Jiang, Yong Liu, Xu Liu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013J (2014) https://doi.org/10.1117/12.2073338

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Non-local means-based nonuniformity correction for infrared focal-plane array detectors Paper

Hui Yu, Zhi-jie Zhang, Fu-sheng Chen, Chen-sheng Wang

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013K (2014) https://doi.org/10.1117/12.2074379

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Sea-level line extraction based on piecewise line detection Paper

Bo Lei, Tingting Ren, Yingbin Liu, Jianwei Yu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013L (2014) https://doi.org/10.1117/12.2074412

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Restoration of non-uniform exposure motion blurred image Paper

Yuanhong Luo, Tingfa Xu, Ningming Wang, Feng Liu

Proceedings Volume International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013M (2014) https://doi.org/10.1117/12.2082837

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